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https://github.com/samaalharbi2/project-data-science-blog-post

A data science project from Udacity’s Nanodegree — exploring what drives developer success
https://github.com/samaalharbi2/project-data-science-blog-post

crisp-dm data-analysis data-science data-visualization nanodegree udacity

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A data science project from Udacity’s Nanodegree — exploring what drives developer success

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# Brains Behind the Code: What Makes a Developer Thrive 🧠

> A deep dive into Stack Overflow's 2024 Developer Survey — uncovering the habits, skills, and behaviors that shape developer success.

## 📖 Table of Contents
- [Business Understanding](#business-understanding)
- [Project Motivation](#project-motivation)
- [Dataset & Link](#dataset--link)
- [Tools & Technologies](#tools--technologies)
- [Methodology](#methodology)
- [Key Findings](#Key--Findings)
- [Acknowledgements](#acknowledgements)
---

## 💼 Business Understanding
CRISP Logo

The goal of this project is to bridge the gap between raw survey data and career-changing insights. We seek to understand how variables such as education, programming languages, and job search behavior influence salary and job outcomes. These findings are crucial for stakeholders such as:

- **Hiring Managers** – To understand talent behavior trends.
- **Developers** – To adjust skills and strategies.
- **Educators** – To tailor tech education programs.
- **Career Coaches** – To guide job seekers based on data.

---

## 🎯 Project Motivation

Why do some developers seem to land jobs faster, earn more, or thrive in diverse tech stacks?
This project aims to explore trends in developer behavior, education, and technology usage to answer questions like:
- How does education affect job search efficiency?
- Which programming languages dominate the industry?
- What does the salary distribution tell us about developer value?

With data from over 80,000 developers worldwide, the goal is to extract actionable insights and uncover patterns that can empower aspiring and current developers to make informed career decisions.

---

## 📂 Dataset & Link

- **Source**: [Kaggle - Stack Overflow Developer Survey 2024](https://www.kaggle.com/datasets/berkayalan/stack-overflow-annual-developer-survey-2024?select=survey_results_public.csv)
- **File Used**: `survey_results_public.csv`

---

## 🛠 Tools & Technologies

- Python
- Pandas, NumPy
- Seaborn, Matplotlib
- Scikit-learn
- Jupyter Notebook

---

## 🔬 Methodology

Our analysis follows the **CRISP-DM** process:

1. **Business Understanding** – Identify the purpose and value of the data.
2. **Data Understanding** – Load, explore, and summarize the data.
3. **Data Preparation** – Clean missing values, transform features.
4. **Modeling** – Train ML models where needed.
5. **Evaluation** – Assess insights/statistics and model performance.
6. **Deployment** – Share findings through visuals and blog storytelling.

---
## 🔍 Key Findings

Based on the analysis of the 2024 Stack Overflow Developer Survey data:

1. **Education Level**: Developers with higher education (master’s or above) tend to have slightly higher salaries, but experience has a stronger impact overall.

2. **Experience and Salary**: Professional coding experience shows a clear positive correlation with salary, especially beyond 5 years.

3. **Most Used Languages**: JavaScript and Python remain the most widely used languages, especially in web and data-related fields.

4. **Remote Work Trends**: The majority of developers (over 60%) prefer hybrid or fully remote work, reflecting current global work trends.

5. **Job Search Time**: Developers with higher education levels tend to spend less time searching for jobs each day.

---
## 🙏 Acknowledgements

Huge thanks to [Stack Overflow](https://stackoverflow.com/) for conducting the survey and [Kaggle](https://www.kaggle.com/) for hosting the data.
This project was built as part of a data science learning journey to demonstrate both technical analysis and storytelling capabilities.